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Author*The author of this computation has been verified*
R Software Modulerwasp_spectrum.wasp
Title produced by softwareSpectral Analysis
Date of computationTue, 09 Dec 2008 03:41:19 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/09/t1228819312m4d3z6hz49eo8je.htm/, Retrieved Sun, 19 May 2024 12:39:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31272, Retrieved Sun, 19 May 2024 12:39:42 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact170
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
F RMP     [Spectral Analysis] [spectral 2] [2008-12-09 10:41:19] [0bb3b56b7083c5944c3818446f605d68] [Current]
Feedback Forum
2008-12-10 19:38:32 [Natalie De Wilde] [reply
Opnieuw zeer beperkt in uitleg.
De Raw Periodogram laat zien dat het langzaam dalend patroon weg is, dit betekent dat de lange termijn trend verdwenen is. Er is niet meteen een patroon te herkennen in de grafiek. Ook de pieken komen niet op regelmatige basis terug.
In de cumulative periodogram zien we ook dat de lange termijn trend verdwenen is. Ook zijn er geen trappen te zien, die op een seizoenale trend duiden.
Een tijdreeks die volledig op toeval berust, geeft een cumulative periodogram die diagonaal is en die volledig binnen het 95% betrouwbaarheidsinterval ligt.
We kunnen inderdaad al een eerste aanwijzing afleiden ivm de ARMA processen. Een cumulative periodogram die afwijkt naar boven, duidt op AR processen, een afwijking naar onder duidt op MA processen.
2008-12-10 19:43:12 [Natalie De Wilde] [reply
step 3: het is niet nodig om de hele tabel in je document te zetten, enkele gegevens zijn voldoende. Ik zie niet meteen dat er een seizoenale trend is als ik kijk naar de tabel alleen, er zijn geen extreem hogere waarden bij 12, 6, 4.
Dit is dan ook de reeds getransformeerde tijdreeks waar seizoenaliteit en lange termijn trend verwijderd zijn.
Je zou wat meer uitleg moeten proberen te geven
2008-12-11 18:43:56 [Loïque Verhasselt] [reply
Step2:Via spectrale analyse: We vinden de juiste output maar niet veel interpretatie. Bij d=0 en D=0. We zien een duidelijk patroon van een lange termijn trend in het begin van de grafiek. We kunnen zien dat ongeveer 70% van de tijdreeks wordt verklaard door de lange termijn trend. We gaan dus al 1 maal niet seizoenaal differentiëren. We zien ook duidelijk een trapsgewijs stijging. Dit wil zeggen dat er duidelijk een patroon aanwezig is van seizoenaliteit. We gaan dus ook 1 maal seizoenaal differentiëren. We zien bij d=1 en D=1 nog een duidelijke afwijking van de diagonaal bij de CP en dit met een redelijk lange periode. Dit heeft waarschijnlijk te maken met een conjunctuur in de tijdreeks. De tijdreeks beschrijft de werkloosheid en is zeker beïnvloed door conjunctuur.


2008-12-11 18:52:30 [Loïque Verhasselt] [reply
Step3: Het was hier de bedoeling om de voorwaarden van stationariteit te controleren via het spectrum en via de ACF. De student geeft alleen maar de output.Wanneer een reeks stationair is, moet ze voldoen aan twee voorwaarden:Eerste voorwaarde: de tijdreeks mag niet geïntegreerd zijn.
Dit wil zeggen dat de ACF (Auto Correlation Function) geen langzaam dalende
niet - seizoenale autocorrelatiecoëfficiënten of seizoenale autocorrelatiecoëfficiënten mag bevatten.Dit impliceert eveneens dat het spectrum geen aanwijzing geeft van (sterke) cyclische golven van lage frequentie (lange periodes)of het spectrum geen (sterke) cyclische golven van seizoenale frequentie vertoont.Tweede voorwaarde: de meest waarschijnlijke verandering door toeval is constant over de tijd. Dit betekent een constante standaardfout over de ganse tijdreeks. Dit impliceert een constante spreiding. Deze conditie is nodig om gemakkelijk te kunnen differentiëren tussen veranderingen te wijten aan toeval, en veranderingen die toegeschreven kunnen worden aan exogene factoren.De eerste voorwaarde is zoals gezegd in step 3, niet voldaan. De tijdreeks vertoont nog seizoenaliteit door de cyclusgebondenheid van werkloosheid.
De tweede voorwaarde is wel voldaan. We hebben door middel van de gevonden lambda - waarde in step 1 de spreiding constant gemaakt. De betrouwbare p – waarde zegt ons dat de regressie helling niet aan het toeval te wijten is, en zo dus significant is.

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Dataseries X:
235.1
280.7
264.6
240.7
201.4
240.8
241.1
223.8
206.1
174.7
203.3
220.5
299.5
347.4
338.3
327.7
351.6
396.6
438.8
395.6
363.5
378.8
357
369
464.8
479.1
431.3
366.5
326.3
355.1
331.6
261.3
249
205.5
235.6
240.9
264.9
253.8
232.3
193.8
177
213.2
207.2
180.6
188.6
175.4
199
179.6
225.8
234
200.2
183.6
178.2
203.2
208.5
191.8
172.8
148
159.4
154.5
213.2
196.4
182.8
176.4
153.6
173.2
171
151.2
161.9
157.2
201.7
236.4
356.1
398.3
403.7
384.6
365.8
368.1
367.9
347
343.3
292.9
311.5
300.9
366.9
356.9
329.7
316.2
269
289.3
266.2
253.6
233.8
228.4
253.6
260.1
306.6
309.2
309.5
271
279.9
317.9
298.4
246.7
227.3
209.1
259.9
266
320.6
308.5
282.2
262.7
263.5
313.1
284.3
252.6
250.3
246.5
312.7
333.2
446.4
511.6
515.5
506.4
483.2
522.3
509.8
460.7
405.8
375
378.5
406.8
467.8
469.8
429.8
355.8
332.7
378
360.5
334.7
319.5
323.1
363.6
352.1
411.9
388.6
416.4
360.7
338
417.2
388.4
371.1
331.5
353.7
396.7
447
533.5
565.4
542.3
488.7
467.1
531.3
496.1
444
403.4
386.3
394.1
404.1
462.1
448.1
432.3
386.3
395.2
421.9
382.9
384.2
345.5
323.4
372.6
376
462.7
487
444.2
399.3
394.9
455.4
414
375.5
347
339.4
385.8
378.8
451.8
446.1
422.5
383.1
352.8
445.3
367.5
355.1
326.2
319.8
331.8
340.9
394.1
417.2
369.9
349.2
321.4
405.7
342.9
316.5
284.2
270.9
288.8
278.8
324.4
310.9
299
273
279.3
359.2
305
282.1
250.3
246.5
257.9
266.5
315.9
318.4
295.4
266.4
245.8
362.8
324.9
294.2
289.5
295.2
290.3
272
307.4
328.7
292.9
249.1
230.4
361.5
321.7
277.2
260.7
251
257.6
241.8
287.5
292.3
274.7
254.2
230
339
318.2
287
295.8
284
271
262.7
340.6
379.4
373.3
355.2
338.4
466.9
451
422
429.2
425.9
460.7
463.6
541.4
544.2
517.5
469.4
439.4
549
533
506.1
484
457
481.5
469.5
544.7
541.2
521.5
469.7
434.4
542.6
517.3
485.7
465.8
447
426.6
411.6
467.5
484.5
451.2
417.4
379.9
484.7
455
420.8
416.5
376.3
405.6
405.8
500.8
514
475.5
430.1
414.4
538
526
488.5
520.2
504.4
568.5
610.6
818
830.9
835.9
782
762.3
856.9
820.9
769.6
752.2
724.4
723.1
719.5
817.4
803.3
752.5
689
630.4
765.5
757.7
732.2
702.6
683.3
709.5
702.2
784.8
810.9
755.6
656.8
615.1
745.3
694.1
675.7
643.7
622.1
634.6
588
689.7
673.9
647.9
568.8
545.7
632.6
643.8
593.1
579.7
546
562.9
572.5




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31272&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31272&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31272&T=0

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The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Raw Periodogram
ParameterValue
Box-Cox transformation parameter (lambda)1
Degree of non-seasonal differencing (d)1
Degree of seasonal differencing (D)1
Seasonal Period (s)12
Frequency (Period)Spectrum
0.0028 (360)28.47367
0.0056 (180)414.292161
0.0083 (120)104.659583
0.0111 (90)527.62959
0.0139 (72)436.831196
0.0167 (60)631.528207
0.0194 (51.4286)5839.526931
0.0222 (45)1169.573349
0.025 (40)5072.18807
0.0278 (36)2213.515735
0.0306 (32.7273)852.336707
0.0333 (30)530.526269
0.0361 (27.6923)11261.18092
0.0389 (25.7143)6978.078336
0.0417 (24)459.614366
0.0444 (22.5)3692.814056
0.0472 (21.1765)2628.95551
0.05 (20)775.979553
0.0528 (18.9474)2893.995714
0.0556 (18)2214.011437
0.0583 (17.1429)3355.14256
0.0611 (16.3636)1307.491068
0.0639 (15.6522)1376.503128
0.0667 (15)267.588572
0.0694 (14.4)51.710806
0.0722 (13.8462)0.898643
0.075 (13.3333)261.375885
0.0778 (12.8571)119.199203
0.0806 (12.4138)87.080052
0.0833 (12)19.728341
0.0861 (11.6129)20.250833
0.0889 (11.25)412.746472
0.0917 (10.9091)55.508656
0.0944 (10.5882)1.792884
0.0972 (10.2857)67.226566
0.1 (10)1059.920249
0.1028 (9.7297)3108.735703
0.1056 (9.4737)139.152789
0.1083 (9.2308)635.633722
0.1111 (9)1.215956
0.1139 (8.7805)1017.652401
0.1167 (8.5714)518.062615
0.1194 (8.3721)975.699483
0.1222 (8.1818)1066.396239
0.125 (8)1180.319748
0.1278 (7.8261)351.203644
0.1306 (7.6596)286.661143
0.1333 (7.5)1571.981167
0.1361 (7.3469)725.70512
0.1389 (7.2)60.092625
0.1417 (7.0588)900.764046
0.1444 (6.9231)667.595856
0.1472 (6.7925)993.521882
0.15 (6.6667)475.721172
0.1528 (6.5455)195.122165
0.1556 (6.4286)98.909622
0.1583 (6.3158)97.311996
0.1611 (6.2069)164.320589
0.1639 (6.1017)98.431157
0.1667 (6)33.698325
0.1694 (5.9016)50.550402
0.1722 (5.8065)375.472754
0.175 (5.7143)8.511937
0.1778 (5.625)160.861268
0.1806 (5.5385)127.439707
0.1833 (5.4545)551.137581
0.1861 (5.3731)297.839469
0.1889 (5.2941)260.703525
0.1917 (5.2174)7.981103
0.1944 (5.1429)1564.389383
0.1972 (5.0704)239.758911
0.2 (5)625.813898
0.2028 (4.9315)2321.90262
0.2056 (4.8649)2869.556434
0.2083 (4.8)1573.859437
0.2111 (4.7368)108.639417
0.2139 (4.6753)935.298211
0.2167 (4.6154)842.467548
0.2194 (4.557)227.504124
0.2222 (4.5)148.088231
0.225 (4.4444)95.643432
0.2278 (4.3902)341.770836
0.2306 (4.3373)536.17233
0.2333 (4.2857)107.567867
0.2361 (4.2353)130.38183
0.2389 (4.186)8.213225
0.2417 (4.1379)745.338556
0.2444 (4.0909)29.698788
0.2472 (4.0449)43.691722
0.25 (4)41.908876
0.2528 (3.956)54.567587
0.2556 (3.913)38.196879
0.2583 (3.871)255.528431
0.2611 (3.8298)16.929041
0.2639 (3.7895)221.37186
0.2667 (3.75)278.820051
0.2694 (3.7113)1154.124681
0.2722 (3.6735)358.15741
0.275 (3.6364)801.474987
0.2778 (3.6)75.938049
0.2806 (3.5644)142.783243
0.2833 (3.5294)356.177064
0.2861 (3.4951)3060.81221
0.2889 (3.4615)20.760888
0.2917 (3.4286)182.723581
0.2944 (3.3962)370.419856
0.2972 (3.3645)63.884539
0.3 (3.3333)117.921087
0.3028 (3.3028)315.866478
0.3056 (3.2727)379.132894
0.3083 (3.2432)345.283894
0.3111 (3.2143)424.96728
0.3139 (3.1858)409.982604
0.3167 (3.1579)145.028319
0.3194 (3.1304)15.430093
0.3222 (3.1034)399.788866
0.325 (3.0769)31.899729
0.3278 (3.0508)62.383933
0.3306 (3.0252)118.884177
0.3333 (3)27.373487
0.3361 (2.9752)21.638867
0.3389 (2.9508)14.244087
0.3417 (2.9268)127.687918
0.3444 (2.9032)28.359501
0.3472 (2.88)112.571672
0.35 (2.8571)1019.932187
0.3528 (2.8346)473.066131
0.3556 (2.8125)489.421993
0.3583 (2.7907)473.937598
0.3611 (2.7692)560.319681
0.3639 (2.7481)2248.32203
0.3667 (2.7273)116.734055
0.3694 (2.7068)238.708351
0.3722 (2.6866)660.480161
0.375 (2.6667)246.379527
0.3778 (2.6471)540.346449
0.3806 (2.6277)1259.722361
0.3833 (2.6087)788.06859
0.3861 (2.5899)196.688116
0.3889 (2.5714)668.642704
0.3917 (2.5532)1188.229112
0.3944 (2.5352)933.439352
0.3972 (2.5175)62.193625
0.4 (2.5)13.350142
0.4028 (2.4828)94.248396
0.4056 (2.4658)50.198259
0.4083 (2.449)81.026515
0.4111 (2.4324)114.513619
0.4139 (2.4161)20.642128
0.4167 (2.4)146.287264
0.4194 (2.3841)44.979104
0.4222 (2.3684)31.638169
0.425 (2.3529)60.237249
0.4278 (2.3377)43.173649
0.4306 (2.3226)589.170987
0.4333 (2.3077)622.959985
0.4361 (2.293)8.900882
0.4389 (2.2785)771.085924
0.4417 (2.2642)1006.968599
0.4444 (2.25)304.823593
0.4472 (2.236)1605.527866
0.45 (2.2222)261.96916
0.4528 (2.2086)505.50468
0.4556 (2.1951)3999.710889
0.4583 (2.1818)718.42606
0.4611 (2.1687)751.190363
0.4639 (2.1557)678.418759
0.4667 (2.1429)933.95044
0.4694 (2.1302)43.074796
0.4722 (2.1176)5855.746814
0.475 (2.1053)32.815179
0.4778 (2.093)1311.654262
0.4806 (2.0809)1699.615978
0.4833 (2.069)159.171774
0.4861 (2.0571)456.965247
0.4889 (2.0455)60.234123
0.4917 (2.0339)167.225704
0.4944 (2.0225)180.46487
0.4972 (2.0112)97.224213
0.5 (2)24.253402

\begin{tabular}{lllllllll}
\hline
Raw Periodogram \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) & 1 \tabularnewline
Degree of non-seasonal differencing (d) & 1 \tabularnewline
Degree of seasonal differencing (D) & 1 \tabularnewline
Seasonal Period (s) & 12 \tabularnewline
Frequency (Period) & Spectrum \tabularnewline
0.0028 (360) & 28.47367 \tabularnewline
0.0056 (180) & 414.292161 \tabularnewline
0.0083 (120) & 104.659583 \tabularnewline
0.0111 (90) & 527.62959 \tabularnewline
0.0139 (72) & 436.831196 \tabularnewline
0.0167 (60) & 631.528207 \tabularnewline
0.0194 (51.4286) & 5839.526931 \tabularnewline
0.0222 (45) & 1169.573349 \tabularnewline
0.025 (40) & 5072.18807 \tabularnewline
0.0278 (36) & 2213.515735 \tabularnewline
0.0306 (32.7273) & 852.336707 \tabularnewline
0.0333 (30) & 530.526269 \tabularnewline
0.0361 (27.6923) & 11261.18092 \tabularnewline
0.0389 (25.7143) & 6978.078336 \tabularnewline
0.0417 (24) & 459.614366 \tabularnewline
0.0444 (22.5) & 3692.814056 \tabularnewline
0.0472 (21.1765) & 2628.95551 \tabularnewline
0.05 (20) & 775.979553 \tabularnewline
0.0528 (18.9474) & 2893.995714 \tabularnewline
0.0556 (18) & 2214.011437 \tabularnewline
0.0583 (17.1429) & 3355.14256 \tabularnewline
0.0611 (16.3636) & 1307.491068 \tabularnewline
0.0639 (15.6522) & 1376.503128 \tabularnewline
0.0667 (15) & 267.588572 \tabularnewline
0.0694 (14.4) & 51.710806 \tabularnewline
0.0722 (13.8462) & 0.898643 \tabularnewline
0.075 (13.3333) & 261.375885 \tabularnewline
0.0778 (12.8571) & 119.199203 \tabularnewline
0.0806 (12.4138) & 87.080052 \tabularnewline
0.0833 (12) & 19.728341 \tabularnewline
0.0861 (11.6129) & 20.250833 \tabularnewline
0.0889 (11.25) & 412.746472 \tabularnewline
0.0917 (10.9091) & 55.508656 \tabularnewline
0.0944 (10.5882) & 1.792884 \tabularnewline
0.0972 (10.2857) & 67.226566 \tabularnewline
0.1 (10) & 1059.920249 \tabularnewline
0.1028 (9.7297) & 3108.735703 \tabularnewline
0.1056 (9.4737) & 139.152789 \tabularnewline
0.1083 (9.2308) & 635.633722 \tabularnewline
0.1111 (9) & 1.215956 \tabularnewline
0.1139 (8.7805) & 1017.652401 \tabularnewline
0.1167 (8.5714) & 518.062615 \tabularnewline
0.1194 (8.3721) & 975.699483 \tabularnewline
0.1222 (8.1818) & 1066.396239 \tabularnewline
0.125 (8) & 1180.319748 \tabularnewline
0.1278 (7.8261) & 351.203644 \tabularnewline
0.1306 (7.6596) & 286.661143 \tabularnewline
0.1333 (7.5) & 1571.981167 \tabularnewline
0.1361 (7.3469) & 725.70512 \tabularnewline
0.1389 (7.2) & 60.092625 \tabularnewline
0.1417 (7.0588) & 900.764046 \tabularnewline
0.1444 (6.9231) & 667.595856 \tabularnewline
0.1472 (6.7925) & 993.521882 \tabularnewline
0.15 (6.6667) & 475.721172 \tabularnewline
0.1528 (6.5455) & 195.122165 \tabularnewline
0.1556 (6.4286) & 98.909622 \tabularnewline
0.1583 (6.3158) & 97.311996 \tabularnewline
0.1611 (6.2069) & 164.320589 \tabularnewline
0.1639 (6.1017) & 98.431157 \tabularnewline
0.1667 (6) & 33.698325 \tabularnewline
0.1694 (5.9016) & 50.550402 \tabularnewline
0.1722 (5.8065) & 375.472754 \tabularnewline
0.175 (5.7143) & 8.511937 \tabularnewline
0.1778 (5.625) & 160.861268 \tabularnewline
0.1806 (5.5385) & 127.439707 \tabularnewline
0.1833 (5.4545) & 551.137581 \tabularnewline
0.1861 (5.3731) & 297.839469 \tabularnewline
0.1889 (5.2941) & 260.703525 \tabularnewline
0.1917 (5.2174) & 7.981103 \tabularnewline
0.1944 (5.1429) & 1564.389383 \tabularnewline
0.1972 (5.0704) & 239.758911 \tabularnewline
0.2 (5) & 625.813898 \tabularnewline
0.2028 (4.9315) & 2321.90262 \tabularnewline
0.2056 (4.8649) & 2869.556434 \tabularnewline
0.2083 (4.8) & 1573.859437 \tabularnewline
0.2111 (4.7368) & 108.639417 \tabularnewline
0.2139 (4.6753) & 935.298211 \tabularnewline
0.2167 (4.6154) & 842.467548 \tabularnewline
0.2194 (4.557) & 227.504124 \tabularnewline
0.2222 (4.5) & 148.088231 \tabularnewline
0.225 (4.4444) & 95.643432 \tabularnewline
0.2278 (4.3902) & 341.770836 \tabularnewline
0.2306 (4.3373) & 536.17233 \tabularnewline
0.2333 (4.2857) & 107.567867 \tabularnewline
0.2361 (4.2353) & 130.38183 \tabularnewline
0.2389 (4.186) & 8.213225 \tabularnewline
0.2417 (4.1379) & 745.338556 \tabularnewline
0.2444 (4.0909) & 29.698788 \tabularnewline
0.2472 (4.0449) & 43.691722 \tabularnewline
0.25 (4) & 41.908876 \tabularnewline
0.2528 (3.956) & 54.567587 \tabularnewline
0.2556 (3.913) & 38.196879 \tabularnewline
0.2583 (3.871) & 255.528431 \tabularnewline
0.2611 (3.8298) & 16.929041 \tabularnewline
0.2639 (3.7895) & 221.37186 \tabularnewline
0.2667 (3.75) & 278.820051 \tabularnewline
0.2694 (3.7113) & 1154.124681 \tabularnewline
0.2722 (3.6735) & 358.15741 \tabularnewline
0.275 (3.6364) & 801.474987 \tabularnewline
0.2778 (3.6) & 75.938049 \tabularnewline
0.2806 (3.5644) & 142.783243 \tabularnewline
0.2833 (3.5294) & 356.177064 \tabularnewline
0.2861 (3.4951) & 3060.81221 \tabularnewline
0.2889 (3.4615) & 20.760888 \tabularnewline
0.2917 (3.4286) & 182.723581 \tabularnewline
0.2944 (3.3962) & 370.419856 \tabularnewline
0.2972 (3.3645) & 63.884539 \tabularnewline
0.3 (3.3333) & 117.921087 \tabularnewline
0.3028 (3.3028) & 315.866478 \tabularnewline
0.3056 (3.2727) & 379.132894 \tabularnewline
0.3083 (3.2432) & 345.283894 \tabularnewline
0.3111 (3.2143) & 424.96728 \tabularnewline
0.3139 (3.1858) & 409.982604 \tabularnewline
0.3167 (3.1579) & 145.028319 \tabularnewline
0.3194 (3.1304) & 15.430093 \tabularnewline
0.3222 (3.1034) & 399.788866 \tabularnewline
0.325 (3.0769) & 31.899729 \tabularnewline
0.3278 (3.0508) & 62.383933 \tabularnewline
0.3306 (3.0252) & 118.884177 \tabularnewline
0.3333 (3) & 27.373487 \tabularnewline
0.3361 (2.9752) & 21.638867 \tabularnewline
0.3389 (2.9508) & 14.244087 \tabularnewline
0.3417 (2.9268) & 127.687918 \tabularnewline
0.3444 (2.9032) & 28.359501 \tabularnewline
0.3472 (2.88) & 112.571672 \tabularnewline
0.35 (2.8571) & 1019.932187 \tabularnewline
0.3528 (2.8346) & 473.066131 \tabularnewline
0.3556 (2.8125) & 489.421993 \tabularnewline
0.3583 (2.7907) & 473.937598 \tabularnewline
0.3611 (2.7692) & 560.319681 \tabularnewline
0.3639 (2.7481) & 2248.32203 \tabularnewline
0.3667 (2.7273) & 116.734055 \tabularnewline
0.3694 (2.7068) & 238.708351 \tabularnewline
0.3722 (2.6866) & 660.480161 \tabularnewline
0.375 (2.6667) & 246.379527 \tabularnewline
0.3778 (2.6471) & 540.346449 \tabularnewline
0.3806 (2.6277) & 1259.722361 \tabularnewline
0.3833 (2.6087) & 788.06859 \tabularnewline
0.3861 (2.5899) & 196.688116 \tabularnewline
0.3889 (2.5714) & 668.642704 \tabularnewline
0.3917 (2.5532) & 1188.229112 \tabularnewline
0.3944 (2.5352) & 933.439352 \tabularnewline
0.3972 (2.5175) & 62.193625 \tabularnewline
0.4 (2.5) & 13.350142 \tabularnewline
0.4028 (2.4828) & 94.248396 \tabularnewline
0.4056 (2.4658) & 50.198259 \tabularnewline
0.4083 (2.449) & 81.026515 \tabularnewline
0.4111 (2.4324) & 114.513619 \tabularnewline
0.4139 (2.4161) & 20.642128 \tabularnewline
0.4167 (2.4) & 146.287264 \tabularnewline
0.4194 (2.3841) & 44.979104 \tabularnewline
0.4222 (2.3684) & 31.638169 \tabularnewline
0.425 (2.3529) & 60.237249 \tabularnewline
0.4278 (2.3377) & 43.173649 \tabularnewline
0.4306 (2.3226) & 589.170987 \tabularnewline
0.4333 (2.3077) & 622.959985 \tabularnewline
0.4361 (2.293) & 8.900882 \tabularnewline
0.4389 (2.2785) & 771.085924 \tabularnewline
0.4417 (2.2642) & 1006.968599 \tabularnewline
0.4444 (2.25) & 304.823593 \tabularnewline
0.4472 (2.236) & 1605.527866 \tabularnewline
0.45 (2.2222) & 261.96916 \tabularnewline
0.4528 (2.2086) & 505.50468 \tabularnewline
0.4556 (2.1951) & 3999.710889 \tabularnewline
0.4583 (2.1818) & 718.42606 \tabularnewline
0.4611 (2.1687) & 751.190363 \tabularnewline
0.4639 (2.1557) & 678.418759 \tabularnewline
0.4667 (2.1429) & 933.95044 \tabularnewline
0.4694 (2.1302) & 43.074796 \tabularnewline
0.4722 (2.1176) & 5855.746814 \tabularnewline
0.475 (2.1053) & 32.815179 \tabularnewline
0.4778 (2.093) & 1311.654262 \tabularnewline
0.4806 (2.0809) & 1699.615978 \tabularnewline
0.4833 (2.069) & 159.171774 \tabularnewline
0.4861 (2.0571) & 456.965247 \tabularnewline
0.4889 (2.0455) & 60.234123 \tabularnewline
0.4917 (2.0339) & 167.225704 \tabularnewline
0.4944 (2.0225) & 180.46487 \tabularnewline
0.4972 (2.0112) & 97.224213 \tabularnewline
0.5 (2) & 24.253402 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31272&T=1

[TABLE]
[ROW][C]Raw Periodogram[/C][/ROW]
[ROW][C]Parameter[/C][C]Value[/C][/ROW]
[ROW][C]Box-Cox transformation parameter (lambda)[/C][C]1[/C][/ROW]
[ROW][C]Degree of non-seasonal differencing (d)[/C][C]1[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D)[/C][C]1[/C][/ROW]
[ROW][C]Seasonal Period (s)[/C][C]12[/C][/ROW]
[ROW][C]Frequency (Period)[/C][C]Spectrum[/C][/ROW]
[ROW][C]0.0028 (360)[/C][C]28.47367[/C][/ROW]
[ROW][C]0.0056 (180)[/C][C]414.292161[/C][/ROW]
[ROW][C]0.0083 (120)[/C][C]104.659583[/C][/ROW]
[ROW][C]0.0111 (90)[/C][C]527.62959[/C][/ROW]
[ROW][C]0.0139 (72)[/C][C]436.831196[/C][/ROW]
[ROW][C]0.0167 (60)[/C][C]631.528207[/C][/ROW]
[ROW][C]0.0194 (51.4286)[/C][C]5839.526931[/C][/ROW]
[ROW][C]0.0222 (45)[/C][C]1169.573349[/C][/ROW]
[ROW][C]0.025 (40)[/C][C]5072.18807[/C][/ROW]
[ROW][C]0.0278 (36)[/C][C]2213.515735[/C][/ROW]
[ROW][C]0.0306 (32.7273)[/C][C]852.336707[/C][/ROW]
[ROW][C]0.0333 (30)[/C][C]530.526269[/C][/ROW]
[ROW][C]0.0361 (27.6923)[/C][C]11261.18092[/C][/ROW]
[ROW][C]0.0389 (25.7143)[/C][C]6978.078336[/C][/ROW]
[ROW][C]0.0417 (24)[/C][C]459.614366[/C][/ROW]
[ROW][C]0.0444 (22.5)[/C][C]3692.814056[/C][/ROW]
[ROW][C]0.0472 (21.1765)[/C][C]2628.95551[/C][/ROW]
[ROW][C]0.05 (20)[/C][C]775.979553[/C][/ROW]
[ROW][C]0.0528 (18.9474)[/C][C]2893.995714[/C][/ROW]
[ROW][C]0.0556 (18)[/C][C]2214.011437[/C][/ROW]
[ROW][C]0.0583 (17.1429)[/C][C]3355.14256[/C][/ROW]
[ROW][C]0.0611 (16.3636)[/C][C]1307.491068[/C][/ROW]
[ROW][C]0.0639 (15.6522)[/C][C]1376.503128[/C][/ROW]
[ROW][C]0.0667 (15)[/C][C]267.588572[/C][/ROW]
[ROW][C]0.0694 (14.4)[/C][C]51.710806[/C][/ROW]
[ROW][C]0.0722 (13.8462)[/C][C]0.898643[/C][/ROW]
[ROW][C]0.075 (13.3333)[/C][C]261.375885[/C][/ROW]
[ROW][C]0.0778 (12.8571)[/C][C]119.199203[/C][/ROW]
[ROW][C]0.0806 (12.4138)[/C][C]87.080052[/C][/ROW]
[ROW][C]0.0833 (12)[/C][C]19.728341[/C][/ROW]
[ROW][C]0.0861 (11.6129)[/C][C]20.250833[/C][/ROW]
[ROW][C]0.0889 (11.25)[/C][C]412.746472[/C][/ROW]
[ROW][C]0.0917 (10.9091)[/C][C]55.508656[/C][/ROW]
[ROW][C]0.0944 (10.5882)[/C][C]1.792884[/C][/ROW]
[ROW][C]0.0972 (10.2857)[/C][C]67.226566[/C][/ROW]
[ROW][C]0.1 (10)[/C][C]1059.920249[/C][/ROW]
[ROW][C]0.1028 (9.7297)[/C][C]3108.735703[/C][/ROW]
[ROW][C]0.1056 (9.4737)[/C][C]139.152789[/C][/ROW]
[ROW][C]0.1083 (9.2308)[/C][C]635.633722[/C][/ROW]
[ROW][C]0.1111 (9)[/C][C]1.215956[/C][/ROW]
[ROW][C]0.1139 (8.7805)[/C][C]1017.652401[/C][/ROW]
[ROW][C]0.1167 (8.5714)[/C][C]518.062615[/C][/ROW]
[ROW][C]0.1194 (8.3721)[/C][C]975.699483[/C][/ROW]
[ROW][C]0.1222 (8.1818)[/C][C]1066.396239[/C][/ROW]
[ROW][C]0.125 (8)[/C][C]1180.319748[/C][/ROW]
[ROW][C]0.1278 (7.8261)[/C][C]351.203644[/C][/ROW]
[ROW][C]0.1306 (7.6596)[/C][C]286.661143[/C][/ROW]
[ROW][C]0.1333 (7.5)[/C][C]1571.981167[/C][/ROW]
[ROW][C]0.1361 (7.3469)[/C][C]725.70512[/C][/ROW]
[ROW][C]0.1389 (7.2)[/C][C]60.092625[/C][/ROW]
[ROW][C]0.1417 (7.0588)[/C][C]900.764046[/C][/ROW]
[ROW][C]0.1444 (6.9231)[/C][C]667.595856[/C][/ROW]
[ROW][C]0.1472 (6.7925)[/C][C]993.521882[/C][/ROW]
[ROW][C]0.15 (6.6667)[/C][C]475.721172[/C][/ROW]
[ROW][C]0.1528 (6.5455)[/C][C]195.122165[/C][/ROW]
[ROW][C]0.1556 (6.4286)[/C][C]98.909622[/C][/ROW]
[ROW][C]0.1583 (6.3158)[/C][C]97.311996[/C][/ROW]
[ROW][C]0.1611 (6.2069)[/C][C]164.320589[/C][/ROW]
[ROW][C]0.1639 (6.1017)[/C][C]98.431157[/C][/ROW]
[ROW][C]0.1667 (6)[/C][C]33.698325[/C][/ROW]
[ROW][C]0.1694 (5.9016)[/C][C]50.550402[/C][/ROW]
[ROW][C]0.1722 (5.8065)[/C][C]375.472754[/C][/ROW]
[ROW][C]0.175 (5.7143)[/C][C]8.511937[/C][/ROW]
[ROW][C]0.1778 (5.625)[/C][C]160.861268[/C][/ROW]
[ROW][C]0.1806 (5.5385)[/C][C]127.439707[/C][/ROW]
[ROW][C]0.1833 (5.4545)[/C][C]551.137581[/C][/ROW]
[ROW][C]0.1861 (5.3731)[/C][C]297.839469[/C][/ROW]
[ROW][C]0.1889 (5.2941)[/C][C]260.703525[/C][/ROW]
[ROW][C]0.1917 (5.2174)[/C][C]7.981103[/C][/ROW]
[ROW][C]0.1944 (5.1429)[/C][C]1564.389383[/C][/ROW]
[ROW][C]0.1972 (5.0704)[/C][C]239.758911[/C][/ROW]
[ROW][C]0.2 (5)[/C][C]625.813898[/C][/ROW]
[ROW][C]0.2028 (4.9315)[/C][C]2321.90262[/C][/ROW]
[ROW][C]0.2056 (4.8649)[/C][C]2869.556434[/C][/ROW]
[ROW][C]0.2083 (4.8)[/C][C]1573.859437[/C][/ROW]
[ROW][C]0.2111 (4.7368)[/C][C]108.639417[/C][/ROW]
[ROW][C]0.2139 (4.6753)[/C][C]935.298211[/C][/ROW]
[ROW][C]0.2167 (4.6154)[/C][C]842.467548[/C][/ROW]
[ROW][C]0.2194 (4.557)[/C][C]227.504124[/C][/ROW]
[ROW][C]0.2222 (4.5)[/C][C]148.088231[/C][/ROW]
[ROW][C]0.225 (4.4444)[/C][C]95.643432[/C][/ROW]
[ROW][C]0.2278 (4.3902)[/C][C]341.770836[/C][/ROW]
[ROW][C]0.2306 (4.3373)[/C][C]536.17233[/C][/ROW]
[ROW][C]0.2333 (4.2857)[/C][C]107.567867[/C][/ROW]
[ROW][C]0.2361 (4.2353)[/C][C]130.38183[/C][/ROW]
[ROW][C]0.2389 (4.186)[/C][C]8.213225[/C][/ROW]
[ROW][C]0.2417 (4.1379)[/C][C]745.338556[/C][/ROW]
[ROW][C]0.2444 (4.0909)[/C][C]29.698788[/C][/ROW]
[ROW][C]0.2472 (4.0449)[/C][C]43.691722[/C][/ROW]
[ROW][C]0.25 (4)[/C][C]41.908876[/C][/ROW]
[ROW][C]0.2528 (3.956)[/C][C]54.567587[/C][/ROW]
[ROW][C]0.2556 (3.913)[/C][C]38.196879[/C][/ROW]
[ROW][C]0.2583 (3.871)[/C][C]255.528431[/C][/ROW]
[ROW][C]0.2611 (3.8298)[/C][C]16.929041[/C][/ROW]
[ROW][C]0.2639 (3.7895)[/C][C]221.37186[/C][/ROW]
[ROW][C]0.2667 (3.75)[/C][C]278.820051[/C][/ROW]
[ROW][C]0.2694 (3.7113)[/C][C]1154.124681[/C][/ROW]
[ROW][C]0.2722 (3.6735)[/C][C]358.15741[/C][/ROW]
[ROW][C]0.275 (3.6364)[/C][C]801.474987[/C][/ROW]
[ROW][C]0.2778 (3.6)[/C][C]75.938049[/C][/ROW]
[ROW][C]0.2806 (3.5644)[/C][C]142.783243[/C][/ROW]
[ROW][C]0.2833 (3.5294)[/C][C]356.177064[/C][/ROW]
[ROW][C]0.2861 (3.4951)[/C][C]3060.81221[/C][/ROW]
[ROW][C]0.2889 (3.4615)[/C][C]20.760888[/C][/ROW]
[ROW][C]0.2917 (3.4286)[/C][C]182.723581[/C][/ROW]
[ROW][C]0.2944 (3.3962)[/C][C]370.419856[/C][/ROW]
[ROW][C]0.2972 (3.3645)[/C][C]63.884539[/C][/ROW]
[ROW][C]0.3 (3.3333)[/C][C]117.921087[/C][/ROW]
[ROW][C]0.3028 (3.3028)[/C][C]315.866478[/C][/ROW]
[ROW][C]0.3056 (3.2727)[/C][C]379.132894[/C][/ROW]
[ROW][C]0.3083 (3.2432)[/C][C]345.283894[/C][/ROW]
[ROW][C]0.3111 (3.2143)[/C][C]424.96728[/C][/ROW]
[ROW][C]0.3139 (3.1858)[/C][C]409.982604[/C][/ROW]
[ROW][C]0.3167 (3.1579)[/C][C]145.028319[/C][/ROW]
[ROW][C]0.3194 (3.1304)[/C][C]15.430093[/C][/ROW]
[ROW][C]0.3222 (3.1034)[/C][C]399.788866[/C][/ROW]
[ROW][C]0.325 (3.0769)[/C][C]31.899729[/C][/ROW]
[ROW][C]0.3278 (3.0508)[/C][C]62.383933[/C][/ROW]
[ROW][C]0.3306 (3.0252)[/C][C]118.884177[/C][/ROW]
[ROW][C]0.3333 (3)[/C][C]27.373487[/C][/ROW]
[ROW][C]0.3361 (2.9752)[/C][C]21.638867[/C][/ROW]
[ROW][C]0.3389 (2.9508)[/C][C]14.244087[/C][/ROW]
[ROW][C]0.3417 (2.9268)[/C][C]127.687918[/C][/ROW]
[ROW][C]0.3444 (2.9032)[/C][C]28.359501[/C][/ROW]
[ROW][C]0.3472 (2.88)[/C][C]112.571672[/C][/ROW]
[ROW][C]0.35 (2.8571)[/C][C]1019.932187[/C][/ROW]
[ROW][C]0.3528 (2.8346)[/C][C]473.066131[/C][/ROW]
[ROW][C]0.3556 (2.8125)[/C][C]489.421993[/C][/ROW]
[ROW][C]0.3583 (2.7907)[/C][C]473.937598[/C][/ROW]
[ROW][C]0.3611 (2.7692)[/C][C]560.319681[/C][/ROW]
[ROW][C]0.3639 (2.7481)[/C][C]2248.32203[/C][/ROW]
[ROW][C]0.3667 (2.7273)[/C][C]116.734055[/C][/ROW]
[ROW][C]0.3694 (2.7068)[/C][C]238.708351[/C][/ROW]
[ROW][C]0.3722 (2.6866)[/C][C]660.480161[/C][/ROW]
[ROW][C]0.375 (2.6667)[/C][C]246.379527[/C][/ROW]
[ROW][C]0.3778 (2.6471)[/C][C]540.346449[/C][/ROW]
[ROW][C]0.3806 (2.6277)[/C][C]1259.722361[/C][/ROW]
[ROW][C]0.3833 (2.6087)[/C][C]788.06859[/C][/ROW]
[ROW][C]0.3861 (2.5899)[/C][C]196.688116[/C][/ROW]
[ROW][C]0.3889 (2.5714)[/C][C]668.642704[/C][/ROW]
[ROW][C]0.3917 (2.5532)[/C][C]1188.229112[/C][/ROW]
[ROW][C]0.3944 (2.5352)[/C][C]933.439352[/C][/ROW]
[ROW][C]0.3972 (2.5175)[/C][C]62.193625[/C][/ROW]
[ROW][C]0.4 (2.5)[/C][C]13.350142[/C][/ROW]
[ROW][C]0.4028 (2.4828)[/C][C]94.248396[/C][/ROW]
[ROW][C]0.4056 (2.4658)[/C][C]50.198259[/C][/ROW]
[ROW][C]0.4083 (2.449)[/C][C]81.026515[/C][/ROW]
[ROW][C]0.4111 (2.4324)[/C][C]114.513619[/C][/ROW]
[ROW][C]0.4139 (2.4161)[/C][C]20.642128[/C][/ROW]
[ROW][C]0.4167 (2.4)[/C][C]146.287264[/C][/ROW]
[ROW][C]0.4194 (2.3841)[/C][C]44.979104[/C][/ROW]
[ROW][C]0.4222 (2.3684)[/C][C]31.638169[/C][/ROW]
[ROW][C]0.425 (2.3529)[/C][C]60.237249[/C][/ROW]
[ROW][C]0.4278 (2.3377)[/C][C]43.173649[/C][/ROW]
[ROW][C]0.4306 (2.3226)[/C][C]589.170987[/C][/ROW]
[ROW][C]0.4333 (2.3077)[/C][C]622.959985[/C][/ROW]
[ROW][C]0.4361 (2.293)[/C][C]8.900882[/C][/ROW]
[ROW][C]0.4389 (2.2785)[/C][C]771.085924[/C][/ROW]
[ROW][C]0.4417 (2.2642)[/C][C]1006.968599[/C][/ROW]
[ROW][C]0.4444 (2.25)[/C][C]304.823593[/C][/ROW]
[ROW][C]0.4472 (2.236)[/C][C]1605.527866[/C][/ROW]
[ROW][C]0.45 (2.2222)[/C][C]261.96916[/C][/ROW]
[ROW][C]0.4528 (2.2086)[/C][C]505.50468[/C][/ROW]
[ROW][C]0.4556 (2.1951)[/C][C]3999.710889[/C][/ROW]
[ROW][C]0.4583 (2.1818)[/C][C]718.42606[/C][/ROW]
[ROW][C]0.4611 (2.1687)[/C][C]751.190363[/C][/ROW]
[ROW][C]0.4639 (2.1557)[/C][C]678.418759[/C][/ROW]
[ROW][C]0.4667 (2.1429)[/C][C]933.95044[/C][/ROW]
[ROW][C]0.4694 (2.1302)[/C][C]43.074796[/C][/ROW]
[ROW][C]0.4722 (2.1176)[/C][C]5855.746814[/C][/ROW]
[ROW][C]0.475 (2.1053)[/C][C]32.815179[/C][/ROW]
[ROW][C]0.4778 (2.093)[/C][C]1311.654262[/C][/ROW]
[ROW][C]0.4806 (2.0809)[/C][C]1699.615978[/C][/ROW]
[ROW][C]0.4833 (2.069)[/C][C]159.171774[/C][/ROW]
[ROW][C]0.4861 (2.0571)[/C][C]456.965247[/C][/ROW]
[ROW][C]0.4889 (2.0455)[/C][C]60.234123[/C][/ROW]
[ROW][C]0.4917 (2.0339)[/C][C]167.225704[/C][/ROW]
[ROW][C]0.4944 (2.0225)[/C][C]180.46487[/C][/ROW]
[ROW][C]0.4972 (2.0112)[/C][C]97.224213[/C][/ROW]
[ROW][C]0.5 (2)[/C][C]24.253402[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31272&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31272&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Raw Periodogram
ParameterValue
Box-Cox transformation parameter (lambda)1
Degree of non-seasonal differencing (d)1
Degree of seasonal differencing (D)1
Seasonal Period (s)12
Frequency (Period)Spectrum
0.0028 (360)28.47367
0.0056 (180)414.292161
0.0083 (120)104.659583
0.0111 (90)527.62959
0.0139 (72)436.831196
0.0167 (60)631.528207
0.0194 (51.4286)5839.526931
0.0222 (45)1169.573349
0.025 (40)5072.18807
0.0278 (36)2213.515735
0.0306 (32.7273)852.336707
0.0333 (30)530.526269
0.0361 (27.6923)11261.18092
0.0389 (25.7143)6978.078336
0.0417 (24)459.614366
0.0444 (22.5)3692.814056
0.0472 (21.1765)2628.95551
0.05 (20)775.979553
0.0528 (18.9474)2893.995714
0.0556 (18)2214.011437
0.0583 (17.1429)3355.14256
0.0611 (16.3636)1307.491068
0.0639 (15.6522)1376.503128
0.0667 (15)267.588572
0.0694 (14.4)51.710806
0.0722 (13.8462)0.898643
0.075 (13.3333)261.375885
0.0778 (12.8571)119.199203
0.0806 (12.4138)87.080052
0.0833 (12)19.728341
0.0861 (11.6129)20.250833
0.0889 (11.25)412.746472
0.0917 (10.9091)55.508656
0.0944 (10.5882)1.792884
0.0972 (10.2857)67.226566
0.1 (10)1059.920249
0.1028 (9.7297)3108.735703
0.1056 (9.4737)139.152789
0.1083 (9.2308)635.633722
0.1111 (9)1.215956
0.1139 (8.7805)1017.652401
0.1167 (8.5714)518.062615
0.1194 (8.3721)975.699483
0.1222 (8.1818)1066.396239
0.125 (8)1180.319748
0.1278 (7.8261)351.203644
0.1306 (7.6596)286.661143
0.1333 (7.5)1571.981167
0.1361 (7.3469)725.70512
0.1389 (7.2)60.092625
0.1417 (7.0588)900.764046
0.1444 (6.9231)667.595856
0.1472 (6.7925)993.521882
0.15 (6.6667)475.721172
0.1528 (6.5455)195.122165
0.1556 (6.4286)98.909622
0.1583 (6.3158)97.311996
0.1611 (6.2069)164.320589
0.1639 (6.1017)98.431157
0.1667 (6)33.698325
0.1694 (5.9016)50.550402
0.1722 (5.8065)375.472754
0.175 (5.7143)8.511937
0.1778 (5.625)160.861268
0.1806 (5.5385)127.439707
0.1833 (5.4545)551.137581
0.1861 (5.3731)297.839469
0.1889 (5.2941)260.703525
0.1917 (5.2174)7.981103
0.1944 (5.1429)1564.389383
0.1972 (5.0704)239.758911
0.2 (5)625.813898
0.2028 (4.9315)2321.90262
0.2056 (4.8649)2869.556434
0.2083 (4.8)1573.859437
0.2111 (4.7368)108.639417
0.2139 (4.6753)935.298211
0.2167 (4.6154)842.467548
0.2194 (4.557)227.504124
0.2222 (4.5)148.088231
0.225 (4.4444)95.643432
0.2278 (4.3902)341.770836
0.2306 (4.3373)536.17233
0.2333 (4.2857)107.567867
0.2361 (4.2353)130.38183
0.2389 (4.186)8.213225
0.2417 (4.1379)745.338556
0.2444 (4.0909)29.698788
0.2472 (4.0449)43.691722
0.25 (4)41.908876
0.2528 (3.956)54.567587
0.2556 (3.913)38.196879
0.2583 (3.871)255.528431
0.2611 (3.8298)16.929041
0.2639 (3.7895)221.37186
0.2667 (3.75)278.820051
0.2694 (3.7113)1154.124681
0.2722 (3.6735)358.15741
0.275 (3.6364)801.474987
0.2778 (3.6)75.938049
0.2806 (3.5644)142.783243
0.2833 (3.5294)356.177064
0.2861 (3.4951)3060.81221
0.2889 (3.4615)20.760888
0.2917 (3.4286)182.723581
0.2944 (3.3962)370.419856
0.2972 (3.3645)63.884539
0.3 (3.3333)117.921087
0.3028 (3.3028)315.866478
0.3056 (3.2727)379.132894
0.3083 (3.2432)345.283894
0.3111 (3.2143)424.96728
0.3139 (3.1858)409.982604
0.3167 (3.1579)145.028319
0.3194 (3.1304)15.430093
0.3222 (3.1034)399.788866
0.325 (3.0769)31.899729
0.3278 (3.0508)62.383933
0.3306 (3.0252)118.884177
0.3333 (3)27.373487
0.3361 (2.9752)21.638867
0.3389 (2.9508)14.244087
0.3417 (2.9268)127.687918
0.3444 (2.9032)28.359501
0.3472 (2.88)112.571672
0.35 (2.8571)1019.932187
0.3528 (2.8346)473.066131
0.3556 (2.8125)489.421993
0.3583 (2.7907)473.937598
0.3611 (2.7692)560.319681
0.3639 (2.7481)2248.32203
0.3667 (2.7273)116.734055
0.3694 (2.7068)238.708351
0.3722 (2.6866)660.480161
0.375 (2.6667)246.379527
0.3778 (2.6471)540.346449
0.3806 (2.6277)1259.722361
0.3833 (2.6087)788.06859
0.3861 (2.5899)196.688116
0.3889 (2.5714)668.642704
0.3917 (2.5532)1188.229112
0.3944 (2.5352)933.439352
0.3972 (2.5175)62.193625
0.4 (2.5)13.350142
0.4028 (2.4828)94.248396
0.4056 (2.4658)50.198259
0.4083 (2.449)81.026515
0.4111 (2.4324)114.513619
0.4139 (2.4161)20.642128
0.4167 (2.4)146.287264
0.4194 (2.3841)44.979104
0.4222 (2.3684)31.638169
0.425 (2.3529)60.237249
0.4278 (2.3377)43.173649
0.4306 (2.3226)589.170987
0.4333 (2.3077)622.959985
0.4361 (2.293)8.900882
0.4389 (2.2785)771.085924
0.4417 (2.2642)1006.968599
0.4444 (2.25)304.823593
0.4472 (2.236)1605.527866
0.45 (2.2222)261.96916
0.4528 (2.2086)505.50468
0.4556 (2.1951)3999.710889
0.4583 (2.1818)718.42606
0.4611 (2.1687)751.190363
0.4639 (2.1557)678.418759
0.4667 (2.1429)933.95044
0.4694 (2.1302)43.074796
0.4722 (2.1176)5855.746814
0.475 (2.1053)32.815179
0.4778 (2.093)1311.654262
0.4806 (2.0809)1699.615978
0.4833 (2.069)159.171774
0.4861 (2.0571)456.965247
0.4889 (2.0455)60.234123
0.4917 (2.0339)167.225704
0.4944 (2.0225)180.46487
0.4972 (2.0112)97.224213
0.5 (2)24.253402



Parameters (Session):
par1 = 1 ; par2 = 1 ; par3 = 1 ; par4 = 12 ;
Parameters (R input):
par1 = 1 ; par2 = 1 ; par3 = 1 ; par4 = 12 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
if (par1 == 0) {
x <- log(x)
} else {
x <- (x ^ par1 - 1) / par1
}
if (par2 > 0) x <- diff(x,lag=1,difference=par2)
if (par3 > 0) x <- diff(x,lag=par4,difference=par3)
bitmap(file='test1.png')
r <- spectrum(x,main='Raw Periodogram')
dev.off()
bitmap(file='test2.png')
cpgram(x,main='Cumulative Periodogram')
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Raw Periodogram',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'Value',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Box-Cox transformation parameter (lambda)',header=TRUE)
a<-table.element(a,par1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degree of non-seasonal differencing (d)',header=TRUE)
a<-table.element(a,par2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degree of seasonal differencing (D)',header=TRUE)
a<-table.element(a,par3)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Seasonal Period (s)',header=TRUE)
a<-table.element(a,par4)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Frequency (Period)',header=TRUE)
a<-table.element(a,'Spectrum',header=TRUE)
a<-table.row.end(a)
for (i in 1:length(r$freq)) {
a<-table.row.start(a)
mylab <- round(r$freq[i],4)
mylab <- paste(mylab,' (',sep='')
mylab <- paste(mylab,round(1/r$freq[i],4),sep='')
mylab <- paste(mylab,')',sep='')
a<-table.element(a,mylab,header=TRUE)
a<-table.element(a,round(r$spec[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')